Search Results for author:
Found 4 papers, 0 papers with code
Evaluation of the Synthetic Electronic Health Records
Generative models have been found effective for data synthesis due to their ability to capture complex underlying data distributions.
Synthesising Electronic Health Records: Cystic Fibrosis Patient Group
Deep generative models are effective data synthesisers due to their ability to capture complex underlying distributions.
Network Generation with Differential Privacy
Differential privacy is a gold standard for data privacy, and the introduction of the differentially private stochastic gradient descent (DP-SGD) algorithm has facilitated the training of private neural models in a number of domains.
A Graph-based Imputation Method for Sparse Medical Records
Our work can facilitate the diagnosis of novel diseases based on the clinical history of past events, with the potential to increase our understanding of the landscape of comorbidities.
